# StratonovichProcess

StratonovichProcess[{a,b},x,t]

represents a Stratonovich process , where .

StratonovichProcess[{a,b,c},x,t]

represents a Stratonovich process , where .

StratonovichProcess[,,{x,x0},{t,t0}]

represents a Stratonovich process with initial condition .

StratonovichProcess[,,,Σ]

uses a Wiener process , with covariance Σ.

StratonovichProcess[proc]

converts proc to a standard Stratonovich process whenever possible.

StratonovichProcess[sdeqns,expr,x,t,wdproc]

represents a Stratonovich process specified by a stochastic differential equation sdeqns, output expression expr, with state x and time t, driven by w following the process dproc.

# Details and Options

• StratonovichProcess is also known as Stratonovich diffusion or stochastic differential equation (SDE).
• StratonovichProcess is a continuous-time and continuous-state random process.
• If the drift a is an -dimensional vector and the diffusion b an ×-dimensional matrix, the process is -dimensional and driven by an -dimensional WienerProcess.
• Common specifications for coefficients a and b include:
•  a scalar, b scalar a scalar, b vector a vector, b vector a vector, b matrix
• A stochastic differential equation is sometimes written as an integral equation .
• The default initial time t0 is taken to be zero, and default initial state x0 is zero.
• The default covariance Σ is the identity matrix.
• A standard Stratonovich process has output , consisting of a subset of differential states .
• Processes proc that can be converted to standard StratonovichProcess form include OrnsteinUhlenbeckProcess, GeometricBrownianMotionProcess, ItoProcess, and StratonovichProcess.
• The stochastic differential equations in sdeqns can be of the form , where is \[DifferentialD], which can be input using dd. The differentials and are taken to be Stratonovich differentials.
• The output expression expr can be any expression involving x[t] and t.
• The driving process dproc can be any process that can be converted to a standard Stratonovich process.
• Method settings in RandomFunction specific to StratonovichProcess include:
•  "EulerMaruyama" Euler–Maruyama (order 1/2, default) "KloedenPlatenSchurz" Kloeden–Platen–Schurz (order 3/2) "Milstein" Milstein (order 1) "StochasticRungeKutta" 3‐stage Rossler SRK scheme (order 1) "StochasticRungeKuttaScalarNoise" 3‐stage Rossler SRK scheme for scalar noise (order 3/2)
• StratonovichProcess can be used with such functions as RandomFunction, CovarianceFunction, PDF, and Expectation.

# Examples

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## Basic Examples(1)

Define a process by its stochastic differential equation:

Simulate the process:

Compute the mean function:

Compute the covariance function:

## Scope(14)

### Basic Uses(9)

Define a Wiener process with drift and diffusion from the sde :

Directly convert from the parametric process:

Define a process , where :

Use differential notation to define the same process:

Define a vector process with output :

Using differential notation:

Define a vector process , where :

Using differential notation:

Define a vector process where :

Using differential notation:

Define a process driven by two correlated Wiener processes:

Define a scalar process corresponding to the sde :

Define vector process and corresponding to the sde and :

Define a process corresponding to the 2D correlated Wiener process:

Define a vector process driven by the correlated 2D Wiener process:

### Special Stratonovich Processes(5)

A Stratonovich process corresponding to the WienerProcess:

A Stratonovich process corresponding to the GeometricBrownianMotionProcess:

A Stratonovich process corresponding to the BrownianBridgeProcess:

A Stratonovich process corresponding to the OrnsteinUhlenbeckProcess:

A Stratonovich process corresponding to the CoxIngersollRossProcess:

## Applications(1)

Define a vector process corresponding to iterated Stratonovich integrals , , , , , :

Compute its mean function:

And its covariance function:

## Properties & Relations(1)

Convert ItoProcess to StratonovichProcess:

Convert back:

## Possible Issues(2)

StratonovichProcess does not support random initial conditions, so cannot be represented:

But it supports processes with fixed initial condition:

Initial time of the driven process needs to match with StratonovichProcess:

With matching initial time, this can be represented:

Wolfram Research (2012), StratonovichProcess, Wolfram Language function, https://reference.wolfram.com/language/ref/StratonovichProcess.html.

#### Text

Wolfram Research (2012), StratonovichProcess, Wolfram Language function, https://reference.wolfram.com/language/ref/StratonovichProcess.html.

#### CMS

Wolfram Language. 2012. "StratonovichProcess." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/StratonovichProcess.html.

#### APA

Wolfram Language. (2012). StratonovichProcess. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/StratonovichProcess.html

#### BibTeX

@misc{reference.wolfram_2021_stratonovichprocess, author="Wolfram Research", title="{StratonovichProcess}", year="2012", howpublished="\url{https://reference.wolfram.com/language/ref/StratonovichProcess.html}", note=[Accessed: 21-January-2022 ]}

#### BibLaTeX

@online{reference.wolfram_2021_stratonovichprocess, organization={Wolfram Research}, title={StratonovichProcess}, year={2012}, url={https://reference.wolfram.com/language/ref/StratonovichProcess.html}, note=[Accessed: 21-January-2022 ]}